BETABiohacksAI is a research tool for informational purposes only. All outputs are computational hypothesis candidates — not confirmed mechanisms, not medical advice, and not a substitute for professional medical judgment. Independent experimental validation is always required.
BiohacksAI is an evolving scientific literature platform. New compounds and evidence are indexed continuously.
B
○
BiohacksAI/Targets/AGMAT/Compounds

Compounds That Target AGMAT

AGMAT · 104 compounds in BiohacksAI corpus

AGMAT (AGMAT) is a biological target with 104 documented compound interactions in the BiohacksAI corpus. The compounds listed below have been identified through computational analysis of BindingDB binding assay data and PubMed literature. Each interaction is ranked by confidence score reflecting the breadth and strength of experimental evidence. This resource supports research into AGMAT modulation for therapeutic and biohacking applications.

View AGMAT target page →
Most Studied Compounds for AGMAT
1
Allium Sativum
500+
studies
2
Centella Asiatica
499+
studies
3
Zingiber Officinale
498+
studies
4
Panax Ginseng
300+
studies
5
Ginkgo Biloba
299+
studies
6
Areca Catechu
199+
studies
7
Smilax China
142+
studies
All 50 Compounds — Ranked by Evidence
1
Agastache Rugosa
1.00
confidence
2
Allium Sativum
500+
studies
1.00
confidence
3
Aloe Vera
1.00
confidence
4
Apis Mellifera
1.00
confidence
5
Arctium Lappa
1.00
confidence
6
Artemisia Capillaris
1.00
confidence
7
Bupleurum Chinense
1.00
confidence
8
Centella Asiatica
499+
studies
1.00
confidence
9
Citrus Reticulata
1.00
confidence
10
Cynomorium Songaricum
1.00
confidence
11
Ephedra Sinica
1.00
confidence
12
Eucommia Ulmoides
1.00
confidence
13
Forsythia Suspensa
1.00
confidence
14
Fritillaria Cirrhosa
1.00
confidence
15
Ginkgo Biloba
299+
studies
1.00
confidence
16
Glycine Max
1.00
confidence
17
Lilium Lancifolium
1.00
confidence
18
Litchi Chinensis
1.00
confidence
19
Lobelia Chinensis
1.00
confidence
20
Lonicera Japonica
1.00
confidence
21
Magnolia Biondii
1.00
confidence
22
Morus Alba
1.00
confidence
23
Nelumbo Nucifera
1.00
confidence
24
Panax Ginseng
300+
studies
1.00
confidence
25
Panax Notoginseng
1.00
confidence
26
Perilla Frutescens
1.00
confidence
27
Polygonum Cuspidatum
1.00
confidence
28
Prunella Vulgaris
1.00
confidence
29
Prunus Armeniaca
1.00
confidence
30
Prunus Persica
1.00
confidence
31
Salvia Miltiorrhiza
1.00
confidence
32
Sargassum Fusiforme
1.00
confidence
33
Scutellaria Baicalensis
1.00
confidence
34
Smilax China
142+
studies
1.00
confidence
35
Vigna Radiata
1.00
confidence
36
Vigna Umbellata
1.00
confidence
37
Zingiber Officinale
498+
studies
1.00
confidence
38
Achyranthes Bidentata
0.50
confidence
39
Aconitum Carmichaelii
0.50
confidence
40
Albizia Julibrissin
0.50
confidence
41
Allium Fistulosum
0.50
confidence
42
Aquilaria Sinensis
0.50
confidence
43
Areca Catechu
199+
studies
0.50
confidence
44
Artemisia Annua
0.50
confidence
45
Artemisia Argyi
0.50
confidence
46
Asparagus Cochinchinensis
0.50
confidence
47
Aster Tataricus
0.50
confidence
48
Atractylodes Macrocephala
0.50
confidence
49
Aucklandia Lappa
0.50
confidence
50
Belamcanda Chinensis
0.50
confidence

The compounds above were identified through computational analysis of BindingDB binding assay data and PubMed literature for AGMAT (AGMAT). Confidence scores reflect the strength and breadth of experimental evidence.

Explore related resources: AGMAT target overview · All biological targets · Biological pathways

Data from BindingDB and PubMed. For research purposes only. Not medical advice.